Authors : G. Silambarasan and J. Anvar Shathik
Abstract: Knowledge base is growing exponentially now a days using different techniques. The ontology has been used widely to integrate the knowledge base for easy retrieval of the web document contents to the user queries. Several steps have been taken in the literatures to integrate the knowledge base which contains the overlapping and complementary information. In this study, we propose a novel technique to knowledge based integration named “automatic ensemble framework for integration of ontology based sematic knowledge base”. It considers the semantic heterogeneous class structures. The proposed framework provides the Solution to the NP hard problem in terms of query selection. Ensemble framework produces the multiple class structures to the knowledge base as knowledge base is large in size and structure matching model is leverages to identify the relationship based on semantic in order to integrate the complex structures of the different KBs. Integrated Knowledge base is been available to access through queries but improper information selection to query leads to complex problem which can be avoided by placing the adaptive query selection algorithm using greedy algorithms. The experimental result demonstrates that proposed model outperforms the state of art approaches in terms of effectiveness, efficiency and accuracy.
G. Silambarasan and J. Anvar Shathik, 2019. Automated Ensemble Framework for Integration of Ontology Based Large Scale Semantic Knowledge Base. Journal of Engineering and Applied Sciences, 14: 399-404.